Fixed asset data online processing method and device, equipment and medium

Abstract

The invention discloses a fixed asset data online processing method and device, equipment and a medium, and the method comprises the steps: obtaining a domain account number corresponding to network equipment assets online, obtaining corresponding login log data according to the domain account number, carrying out the login data matching of the login log data and a preset asset checking configuration table, and carrying out the login data matching of the login log data and the preset asset checking configuration table. And finally, updating the preset asset checking configuration table matched with the login log data into an effective checking asset table, thereby solving the problem that online checking is carried out on network equipment through interaction analysis among a specific checking command, an equipment response log and a checking service workstation in the prior art; therefore, the technical problems of low checking efficiency and high checking cost are solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device, equipment and medium for online processing of fixed asset data. Background Art

[0002] Fixed asset inventory refers to the process of counting, checking and evaluating the fixed assets owned by an enterprise or organization. Fixed assets usually include buildings, machinery and equipment, vehicles, furniture, computers and other items that are used for a long time and have high value. The purpose of inventory is to ensure that the book records are consistent with the actual assets owned, and to evaluate the value and condition of the assets. Ensure the authenticity and accuracy of assets: verify whether the number, specifications, models, etc. of fixed assets actually owned by the enterprise are consistent with the records on the books. Discover the profit and loss of assets: timely discover the surplus and shortage of assets in order to make corresponding accounting treatment and management adjustments. Assess the status of assets: understand the use status, degree of wear and tear and maintenance needs of fixed assets, and provide a basis for the repair, renewal and disposal of assets. Strengthen asset management: improve the efficiency of asset use, prevent the loss and waste of assets, and ensure the safety and integrity of corporate assets.

[0003] Currently, fixed asset inventory mainly adopts RFID electronic tag inventory and on-site manual inventory. On-site manual inventory requires asset managers to count assets on site, which takes a long time. RFID electronic tags need to be coded and labeled for each fixed asset in the early stage, as well as RFID inventory handheld devices, which require a large amount of manpower and inventory equipment costs. For network equipment assets in niche areas, such as computers and servers with networking functions, the industry has conducted online inventory of network equipment through specific inventory commands, equipment response logs and interactive analysis between inventory service workstations. This method is not flexible enough and the implementation process is relatively complicated.

[0004] Therefore, the above-mentioned existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations leads to low inventory efficiency and high inventory costs, which are technical problems that need to be solved urgently. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a method, device, equipment and medium for online processing of fixed asset data that can be applied to machine learning or other related fields, aiming to solve the problems of low inventory efficiency and high inventory cost caused by the existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations.

[0006] The technical solution of the present invention is as follows:

[0007] The present invention provides a method for online processing of fixed asset data, which comprises:

[0008] Obtaining the domain account corresponding to the network device asset online, and obtaining corresponding login log data according to the domain account;

[0009] Matching the login log data with the preset asset inventory configuration table;

[0010] The preset asset inventory configuration table after matching the login log data is updated to a valid inventory asset table.

[0011] Optionally, the step of obtaining a domain account corresponding to a network device asset online, and obtaining corresponding login log data according to the domain account, includes:

[0012] Online synchronous acquisition of domain accounts corresponding to network equipment assets;

[0013] The login log data corresponding to the domain account at a first preset time node is obtained.

[0014] Optionally, the step of obtaining the login log data corresponding to the domain account at the first preset time node further includes:

[0015] Cleaning and processing the login log data to determine that the login log data is valid login log data;

[0016] The valid login log data is stored in the login data reference table in an accumulative manner.

[0017] Optionally, the step of cleaning the login log data and determining that the login log data is valid login log data includes:

[0018] Clean and process the login log data according to preset field rules using a data synchronization tool;

[0019] Determine that the login log data is valid login log data.

[0020] Optionally, the step of matching the login log data with the preset asset inventory configuration table includes:

[0021] Configure the asset inventory configuration table according to the obtained online inventory validity days and inventory effectiveness flag;

[0022] The valid login log data is matched with the asset inventory configuration table.

[0023] Optionally, the step of performing login data matching between the valid login log data and the asset inventory configuration table includes:

[0024] Mapping the unique identification code of the valid login log data according to the acquired current inventory instruction;

[0025] According to the unique identification code, the valid login log data corresponding to the valid days of the online inventory is matched with the asset inventory configuration table.

[0026] Optionally, the step of updating the preset asset inventory configuration table after matching the login log data to a valid asset inventory table specifically includes:

[0027] Updating the inventory time of the login log data and marking the inventory effectiveness mark;

[0028] The preset asset inventory configuration table after update and matching is a valid asset inventory table.

[0029] On the other hand, this embodiment further provides a fixed asset data online processing device, including:

[0030] A login log data module, used to obtain the domain account corresponding to the network device asset online, and obtain the corresponding login log data according to the domain account;

[0031] A matching module, used to match the login log data with the preset asset inventory configuration table;

[0032] An updating module is used to update the preset asset inventory configuration table after matching the login log data to a valid inventory asset table.

[0033] Optionally, the login log data module includes:

[0034] The domain account submodule is used to obtain the domain account corresponding to the network device assets online and synchronously;

[0035] The login log data submodule is used to obtain the login log data corresponding to the domain account at a first preset time node.

[0036] Optionally, it also includes:

[0037] A login log data cleaning module, used for cleaning and processing the login log data, and determining that the login log data is valid login log data;

[0038] The login log data storage module is used to store the valid login log data in a login data reference table in an accumulative manner.

[0039] Optionally, the login log data cleaning module is specifically used to clean and process the login log data according to preset field rules through a data synchronization tool to determine that the login log data is valid login log data.

[0040] Optionally, the matching module includes:

[0041] The configuration submodule is used to configure the asset inventory configuration table according to the obtained online inventory effective days and inventory effective identification;

[0042] The matching submodule is used to perform login data matching between the valid login log data and the asset inventory configuration table.

[0043] Optionally, the matching submodule is specifically used to map the unique identification code of the valid login log data according to the acquired current inventory instruction, and match the valid login log data corresponding to the valid days of the online inventory with the asset inventory configuration table according to the unique identification code.

[0044] Optionally, the update module includes:

[0045] A first updating submodule, used for updating the inventory time of the login log data and marking the inventory effective mark;

[0046] The second updating submodule is used to update the matched preset asset inventory configuration table to a valid inventory asset table.

[0047] On the other hand, this embodiment further provides a fixed asset data online processing device, the device comprising at least one processor; and

[0048] a memory communicatively connected to the at least one processor; wherein,

[0049] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned fixed asset data online processing method.

[0050] On the other hand, this embodiment also provides a non-volatile computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by one or more processors, the one or more processors can execute the above-mentioned fixed asset data online processing method.

[0051] Beneficial effect: The present invention discloses a method, device, equipment and medium for online processing of fixed asset data. Compared with the prior art, the present invention obtains the domain account corresponding to the network device asset online, obtains the corresponding login log data according to the domain account, and then matches the login log data with the preset asset inventory configuration table, and finally updates the preset asset inventory configuration table after the login log data is matched to a valid inventory asset table, thereby solving the technical problems of low inventory efficiency and high inventory cost caused by the existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations.

[0052] The present invention obtains corresponding login log data through domain accounts to perform online detection of computer assets, which can improve data utilization, perform fully automatic inventory, greatly improve asset inventory efficiency, reduce enterprise operating costs, and improve computer asset data management level. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0054] Figure 1 A flow chart of a method for online processing of fixed asset data provided by an embodiment of the present invention;

[0055] Figure 2 A schematic diagram of the functional modules of the online fixed asset data processing device provided by an embodiment of the present invention;

[0056] Figure 3 A schematic diagram of the hardware structure of a fixed asset data online processing device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail below. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. The embodiments of the present invention are described below in conjunction with the accompanying drawings.

[0058] The online processing of fixed asset data mentioned in the present invention is based on the existing RFID technology to obtain asset data information of the assets to be counted for multi-terminal interaction to realize inventory. RFID (Radio Frequency Identification) is a wireless communication technology that identifies and tracks objects with electronic tags through radio waves. RFID systems usually consist of two main parts: RFID tags (or smart tags) and RFID readers. RFID tags are small electronic devices that contain a miniature radio frequency circuit and a chip that stores information. Tags can be passive (no power supply, obtain energy from the reader) or active (with built-in power supply). The information on the tag can be unique and used to identify a single item. An RFID reader is a device that emits radio waves and receives signals from RFID tags. The reader can be fixed or portable and is used to read tag information within a certain range. Its working principle is to transmit signals: the RFID reader emits radio waves. Tag activation: After the RFID tag receives the signal, if it is a passive tag, it will obtain energy from the reader's signal. Data transmission: The tag sends the stored information back to the reader by reflection or echo. Information processing: After the reader receives the information, it transmits it to the computer system for processing.

[0059] Therefore, the existing fixed asset inventory based on RFID technology includes: obtaining the asset number of the asset to be counted based on RFID technology; the server obtains the asset information to be counted from the user end according to the inventory task as inventory data; the server includes an asset module, an inventory task module, a data transmission module, and an inventory data module; the asset module records the asset numbers of all assets in the form of a list; the inventory task module extracts the asset number of the asset to be counted from the inventory task, and determines the inventory path based on the ant colony algorithm within the asset range recorded in the asset module; the server obtains the asset information to be counted as inventory data according to the inventory path output by the inventory task module; the inventory data is stored in the inventory data module after passing through the data transmission module. This multi-terminal interaction and data transmission collaboration require a large amount of manpower and inventory equipment costs, and the implementation process is relatively complicated, the equipment is prone to technical problems, and the cost is high.

[0060] In order to solve the above-mentioned problems, the present invention proposes a method for online processing of fixed asset data. Figure 1 , Figure 1 The present invention provides a flowchart of an embodiment of the method for online processing of fixed asset data.

[0061] The fixed asset data online processing method provided in this embodiment is applied to mobile devices and fixed terminal devices based on artificial intelligence, and the terminal operating system thereof may include a handheld device operating system (iPhone operating system, iOS system), an Android system or other operating systems, including but not limited to smart phones, tablet computers, portable computers and desktop servers, etc. Figure 1 As shown, the method specifically comprises the following steps:

[0062] S101, obtaining a domain account corresponding to a network device asset online, and obtaining corresponding login log data according to the domain account;

[0063] In this embodiment, for network device assets such as physical computer assets, there are technical means to perform online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations, but the efficiency is low. Therefore, it is first necessary to obtain the domain account corresponding to the network device asset online, and obtain the corresponding login log data based on the domain account.

[0064] It can be understood that, in one embodiment, obtaining the domain account corresponding to the network device asset online, and obtaining the corresponding login log data according to the domain account includes:

[0065] Online synchronous acquisition of domain accounts corresponding to network equipment assets;

[0066] The login log data corresponding to the domain account at a first preset time node is obtained.

[0067] In this embodiment, the computer login log data of the domain account management platform must first be synchronized through KETTLE. The log data mainly involves the domain account of the login person, login time, computer SN code, and computer name.

[0068] For example, a computer domain account refers to an account used in a Windows domain environment. A Windows domain is a security boundary in a network that defines a group of computers and users that share the same security policies, user accounts, and resource access rights. Computer domain accounts can be: Centrally managed: Domain accounts can be centrally managed by domain administrators, including account creation, deletion, and permission assignment. Single sign-on (SSO): After a user logs in with a domain account, they can access all resources in the domain without having to repeatedly enter their account and password. Security: Domain accounts are often combined with complex password policies and security policies to improve security. Group Policy: Domain administrators can apply group policies to control user and computer behavior, such as software installation, security settings, desktop settings, etc. Resource access: Domain accounts allow users to access files, printers, and other resources managed on domain controllers. Authentication: Domain accounts are used for network authentication to ensure that only authorized users can access network resources. Domain controller: A domain controller is a server that manages domain accounts and other domain services. Active Directory: In a Windows environment, Active Directory is a directory service used to manage domain accounts and other objects in a domain. OU (Organizational Unit): In Active Directory, OU is a logical grouping for managing domain accounts and other objects. Permission inheritance: The permissions of domain accounts can be inherited through OU and group policy, which simplifies permission management.

[0069] At the same time, obtaining the corresponding login log data through the domain account refers to the data obtained by monitoring and recording the behavior of users logging into the system using domain accounts in the network environment of an enterprise or organization. In addition to online processing of fixed asset data, these data can also be used in security audits, user behavior analysis, system security maintenance, etc.

[0070] Specifically, it can be, Security audit: Login logs can help auditors check whether there are unauthorized access attempts or abnormal login behaviors. User behavior analysis: By analyzing login logs, you can understand the user's login habits, such as login time, frequency, and the device used. System security maintenance: Regularly checking login logs can help discover potential security threats, such as brute force cracking attempts or account abuse. Compliance requirements: Certain industry standards and regulations require the recording and retention of login logs to meet compliance requirements. Incident response: When a security incident occurs, login logs can be used as part of the investigation to help determine the source and scope of the incident. Resource allocation: By analyzing login logs, you can understand which resources are most frequently accessed, thereby optimizing resource allocation and load balancing. User support: Login logs can help support solve user login problems, such as forgotten passwords or account lockouts. Performance monitoring: Login logs can provide insights into system performance, such as login response time and system load. Data leakage prevention: Monitoring login logs can help prevent data leakage and identify potential internal or external threats by detecting abnormal login patterns. User education: By analyzing login logs, you can identify user groups that need to strengthen security awareness, so as to provide targeted security training.

[0071] In order to effectively utilize login log data, it is usually necessary to use log management tools and security information and event management (SIEM) systems to automate log collection, analysis, and alerts. These tools can help quickly identify and respond to potential security issues. At the same time, it is also very important to ensure the secure storage and access control of login logs to prevent sensitive information leakage.

[0072] The aforementioned Kettle, (Pentaho Data Integration (PDI)), is an ETL (Extract, Transform, Load) tool for data integration, data migration, and data cleaning. The main features of Kettle include: Flexibility: Supports a variety of data sources and targets, including relational databases, file systems, APIs, etc. Visualization: Provides a graphical user interface where users can design ETL processes by dragging and dropping components. Extensibility: Functionality can be extended through plug-ins and custom scripts. Cross-platform: Can run on a variety of operating systems, including Windows, Linux, and Mac OS. Community support: Has an active community where users can seek help and share experiences. Kettle is used in data warehouses, data migration, data cleaning, and data integration. It provides a rich variety of transformations and job types, allowing users to perform complex data processing tasks.

[0073] The aforementioned computer's SN code, or serial number, is a unique identification code assigned by the manufacturer to each computer. This serial number is specifically used in the following aspects: Product identification: The SN code is a unique identifier for each computer and is used to distinguish different devices. Technical support: When a user needs technical support, providing the SN code can help service personnel quickly find the computer's configuration information and history. Anti-theft tracking: If the computer is lost or stolen, the SN code can help track the device. Product registration: After purchasing a computer, the user can register the product on the manufacturer's website using the SN code to obtain additional services or discounts. Software activation: Some software products may require the computer's SN code to be entered to verify the hardware and activate the software. Asset management: Enterprises or organizations use SN codes to manage their hardware assets to ensure that each device is recorded and tracked. Quality control: If a batch of computers has a manufacturing defect, the manufacturer can use the SN code to track and recall the affected products.

[0074] The aforementioned acquisition of the login log data corresponding to the domain account at the first preset time node is because the following further includes:

[0075] Cleaning and processing the login log data to determine that the login log data is valid login log data;

[0076] The valid login log data is stored in the login data reference table in an accumulative manner.

[0077] In this embodiment, it is necessary to set a scheduled task (i.e., the first preset time node), clean the computer login log data regularly every day, and accumulate and update the valid login log data to the computer login data reference table, where the reference table fields include: the domain account of the most recent login, the most recent login time, the computer SN code, the cumulative number of login days and the computer name.

[0078] The aforementioned cleaning process of the login log data is an important part of data preprocessing, which involves identifying and correcting errors and inconsistencies in the data to improve data quality. The purpose of data cleaning is to ensure the accuracy, completeness and consistency of the data, which is crucial for tasks such as data analysis, data mining and machine learning. It can be the following operations: Missing value processing: Delete records with missing values. Fill missing values, such as using the mean, median, mode or prediction model. Outlier detection and processing: Use statistical methods (such as standard deviation, box plot) or machine learning algorithms to identify outliers. Decide whether to delete outliers, correct them or keep them (if they are valid data points). Data format standardization: Ensure that all data follows the same format, such as date format, currency symbol, number format, etc. Data type conversion: Convert data to a format suitable for analysis, such as converting text to numeric values. Data deduplication: Identify and delete duplicate records. Data consistency check: Ensure that the data is logically consistent, for example, the gender field should not contain values ​​that are neither male nor female. Spelling and grammar correction: Correct spelling errors and grammatical errors in text data. Data merging: Merge data from different sources into a unified dataset. Data segmentation: Split data into multiple parts for easier management and analysis. Data encoding: Convert categorical data into numerical representations, such as One-Hot Encoding. Regular expressions: Use regular expressions to identify and extract specific patterns in text data.

[0079] The aforementioned data cleaning processing operations can be implemented through data cleaning algorithms, including but not limited to the following methods: For example, missing value processing: Prediction model: Use machine learning models (such as regression, decision tree) to predict missing values. Outlier detection: Use statistical methods such as Z-scores and IQR (interquartile range) to identify outliers, use visualization tools such as box plots and scatter plots to identify outliers, and use algorithms such as Isolation Forest and DBSCAN to detect outliers. Data deduplication: Exact matching: Directly compare whether the records are exactly the same. Fuzzy matching: Use string similarity algorithms (such as Levenshtein distance) to identify similar records. Data format standardization: Date format: Unify dates of different formats into a standard format. Number format: Unify the representation of numbers, such as decimal points and thousands separators. Text format: Unify the case, spaces, and special characters of text. Data type conversion: Text to number: Convert text data to numeric types, such as converting "male / female" to 0 / 1. Categorical to numerical: Use One-Hot Encoding or Label Encoding to convert categorical data to numerical values. Data consistency check: Range check: Make sure the data is within a reasonable range, such as age should not be negative. Logic check: Check the logical relationship between data, such as users with the "married" status should not be marked as "yes" in the "single" column. Spelling and grammar correction: Autocorrection: Use natural language processing libraries such as NLTK, SpaCy for spelling and grammar correction. Regular expressions: Data extraction: Use regular expressions to extract data with specific patterns from text. Data validation: Use regular expressions to validate data formats such as email addresses, phone numbers. Data merging: Vertical merging: Merge multiple datasets by rows. Horizontal merging: Merge multiple datasets by columns. Data encoding: Label encoding: Convert categorical variables to numerical labels. One-hot encoding: Create a new column for each category of a categorical variable. Data transformation: Normalization: Scale the data to a specific range, such as 0 to 1. Standardization: Convert the data to a distribution with zero mean and unit variance.

[0080] Therefore, in this embodiment, the steps of cleaning and processing the login log data and determining that the login log data is valid login log data include: cleaning and processing the login log data according to preset field rules through a data synchronization tool; and determining that the login log data is valid login log data.

[0081] The aforementioned data cleaning can also use tools other than kettle: such as Pandas and OpenRefine. Pandas is a Python data analysis library that provides high-performance, easy-to-use data structures and data analysis tools. Pandas is particularly suitable for processing tabular data, time series data, and more complex data analysis tasks. Data structure: Series: a one-dimensional labeled array that can contain any data type. DataFrame: a two-dimensional labeled data structure, similar to an Excel table, with rows and columns. Data import and export: supports importing data from multiple formats such as CSV, Excel, SQL database, JSON, etc. Data can be exported to formats such as CSV, Excel, JSON, etc. Data cleaning: handles missing data, data type conversion, data deduplication, etc. Data merging and connection: supports a variety of merging and connection operations, such as merge, join, concat, etc. Data grouping: use the groupby function to group data for easy aggregation operations, where the groupby function can group data sets and then apply aggregation, transformation, or filtering functions to each group. Data aggregation: provides a rich aggregation function, such as sum, mean, count, etc. Time series analysis: Powerful time series processing capabilities, including time indexing, frequency conversion, moving windows, etc.

[0082] OpenRefine is a powerful tool for processing and cleaning messy data. It provides a user-friendly interface that allows users to explore, clean and transform data without programming knowledge. Main features and functions: Data import: supports importing multiple data formats, including CSV, TSV, JSON, XML, Excel, etc. Data cleaning: can identify and handle common problems in data, such as inconsistent formats, duplicate values, missing values, etc. Data conversion: provides a variety of data conversion functions, including text conversion, date format conversion, number formatting, etc. Data clustering: through clustering algorithms, it can help users identify and merge similar but not identical data items. Data export: cleaned and converted data can be exported to multiple formats for subsequent use. Undo / redo function: provides an operation history, which can undo or redo operations at any time. Extensibility: By installing extensions, you can increase the functionality of OpenRefine, such as connecting to external databases, using regular expressions, etc. Interactive operation: users can complete most operations by clicking and selecting, making the data cleaning process more intuitive and simple. Data association: can be associated with other datasets or online databases to enrich the information of the dataset. Custom export settings: Allows users to customize the exported data format and content as needed. OpenRefine is a Java-based application that can run on multiple operating systems.

[0083] S102, matching the login log data with the preset asset inventory configuration table;

[0084] In this embodiment, the login log data is cleaned and processed according to preset field rules by a data synchronization tool. After determining that the login log data is valid login log data, the login log data needs to be matched with the preset asset inventory configuration table.

[0085] Specifically, in one embodiment, the asset inventory configuration table may be configured according to the acquired online inventory effective days and inventory effectiveness identification, and the valid login log data may be matched with the asset inventory configuration table.

[0086] Among them, the asset inventory configuration table is configured according to the obtained online inventory effective days and inventory effective identification, which is specifically used for computer asset inventory identification rule judgment, so that the asset inventory configuration table can include effective inventory judgment days and rule effective identification. For example, in the inventory module of the fixed asset management system, the system administrator enters the online inventory effective days of 3 days on the system inventory rule configuration page, that is, the inventory list created in the system will be marked to match the latest login time of the online terminal login data, and only the latest login time and the inventory matching day (daily scheduled matching) within 3 days are taken as valid inventory.

[0087] As mentioned above, the valid login log data is matched with the asset inventory configuration table by creating an inventory list in the fixed asset management system to trigger the inventory task. At this time, the inventory task is mapped and matched with the computer login data reference table according to the SN code of the computer asset in the inventory list and the domain account information of the person responsible for the asset. Within the valid days, it is marked as inventoryed, and the inventory person is the domain account login user who recently logged in to the computer asset. Otherwise, it is not inventoryed. Enter the next round of inventory matching according to the new login record. For example, when the company conducts an annual inventory, the company's fixed asset manager can create an inventory list in the inventory management module of the fixed asset management system. In the process of creating the inventory list, the user needs to select the estimated completion time of the inventory, select the computer assets to be inventoried, and save the created inventory list. The system will automatically trigger the online inventory task, and match the data according to the valid inventory days set by the system and the computer login situation in the computer login record reference table. For the computer asset that is earlier than the latest login time of the current matching day minus the valid inventory days, it can be marked as inventoryed. The system regularly updates the computer domain account login records every day, and re-matches the computer assets that have not been successfully matched based on the latest login records.

[0088] S103: Update the preset asset inventory configuration table after matching the login log data to a valid inventory asset table.

[0089] The step of updating the preset asset inventory configuration table after matching the login log data to a valid asset inventory table specifically includes:

[0090] Updating the inventory time of the login log data and marking the inventory effectiveness mark;

[0091] The preset asset inventory configuration table after update and matching is a valid asset inventory table.

[0092] In this embodiment, the SN code of the computer asset is used as a unique identifier, and the current login records of the last 30 days are compared with the reference table, and the latest login information, the latest login time, and the cumulative login days are updated. Kettle synchronizes the latest login records on a daily basis, and the storage process updates the login record reference table data according to the latest login records. This is used for subsequent computer asset inventory matching within the enterprise.

[0093] It can be understood that in one embodiment, it is first determined whether the SN code exists in the login log data table. If so, the login time and the number of login record days are updated and added by one day. If not, the SN code is inserted into the login log data table, and the number of login days is initialized to 1 day. Finally, an updated login log data table is generated.

[0094] The aforementioned login log data refers to the data generated when a user logs into a system, application, or network resource. This data is very important for security monitoring, user behavior analysis, system maintenance, and troubleshooting. Login logs usually contain the following information: Timestamp: records the specific date and time when the login attempt occurred. User identification: records the username or user ID of the user who attempted to log in. Login status: records whether the login attempt was successful, and the reason for the failure (such as wrong password, account locked, etc.). Source IP address: records the IP address from which the login attempt was initiated, which helps to identify the login location. Login location: may include information such as country, city, ISP (Internet service provider), etc. Device used: records the type of device used for the login attempt (such as PC, mobile phone, tablet, etc.). Operating system and browser information: records the version information of the user's operating system and browser. Login method: records the login method used by the user, such as password, biometrics, multi-factor authentication, etc. Session ID: records the unique identifier of the login session, which helps to track the user's activities in the system. Associated activities: records the activities performed by the user after login, such as resources accessed, operations performed, etc.

[0095] The inventory counting rules mentioned in one embodiment can be standardized processes and guidelines to ensure the accuracy and efficiency of the inventory counting process. These rules generally include the following aspects: Inventory counting plan: determine the frequency of inventory counting (such as annual, quarterly or monthly). Develop a detailed inventory counting schedule and process. Responsibility allocation: clarify who is responsible for each link of the inventory counting, including preparation before the inventory counting, actual inventory counting and data processing after the inventory counting. Inventory counting scope: determine which assets need to be counted, including fixed assets, inventory, tools, etc. Data verification: after the inventory counting, how to verify whether the actual inventory counting results are consistent with the book records. Difference handling: determine how to deal with differences found in the inventory counting, including investigating the causes, adjusting accounts and taking preventive measures. Inventory report: specify how to prepare the inventory counting report, including the content, format and distribution of the report. Inventory audit: determine whether the inventory counting process needs to be audited, as well as the audit process and standards.

[0096] Therefore, in this embodiment, after the matching preset asset inventory configuration table is updated to be a valid inventory asset table, an inventory report can also be generated online, which can be achieved through a variety of tools that provide a visual interface, allow data to be entered and templates to be selected, and then automatically generate professional reports. For example, AiBro Report Generator: This is an artificial intelligence-based report generation tool that can automatically generate work summaries, learning summaries, daily, weekly and monthly reports, etc. Users only need to enter key information, and AI can help quickly complete report writing. It is suitable for users who need to quickly generate educational theme reports because it can process and analyze large amounts of data, provide in-depth analysis and insights, and support multiple output formats. Bar Chart Online Generator: If your inventory report needs to include data visualization, this tool can help you quickly create a bar chart. Users only need to enter data, and the system will automatically generate a chart, and support real-time preview and export to image format. This is very useful for showing data distribution and proportional relationships in reports. AI Report Generator: This tool can automatically generate various types of documents such as work daily reports, weekly reports, monthly reports, and learning summaries. It uses AI technology to quickly complete report writing by entering key information, saving time and improving efficiency.

[0097] Inventory report PPT template: If you need to make a PPT for an inventory report, this resource provides PPT templates in a variety of styles, including business, simple, cartoon, etc., which can help you quickly create a professional inventory report presentation.

[0098] In this embodiment, the computer power on / off login status of employees in the enterprise is collected through the domain account management platform every day, and the log data is cleaned regularly every day to obtain valid records; the effective computer login records are deduplicated and analyzed every day, and the continuous login records of the past 30 days and the latest login time and login person information are accumulated and recorded according to the computer's SN code to form a login data reference table; at the same time, an inventory matching rule table is implemented to determine the recent login days as valid inventory data, so that the inventory rules can be flexibly configured in the later stage; finally, the domain account of the personnel information of the computer assets in the fixed asset system is matched with the login person information in the computer login data reference table to identify the inventory status of the computer assets. This method can greatly reduce the inventory cost of computer assets and improve the timeliness of inventory, with flexible configuration of inventory rules, accurate inventory information and strong usability.

[0099] The method for online processing of fixed asset data provided in this embodiment obtains the domain account corresponding to the network device asset online, obtains the corresponding login log data according to the domain account, then matches the login log data with the preset asset inventory configuration table, and finally updates the preset asset inventory configuration table after the login log data matching to a valid inventory asset table, thereby solving the technical problems of low inventory efficiency and high inventory cost caused by the existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations.

[0100] This embodiment obtains corresponding login log data through domain accounts to perform online detection of computer assets, which can improve data utilization and perform fully automatic inventory, greatly improving asset inventory efficiency, reducing enterprise operating costs, and improving computer asset data management level.

[0101] Furthermore, by using a data synchronization tool to clean and process the login log data according to preset field rules, the operational data within the enterprise (domain account login records) is cleaned and standardized, and used for online inventory of computer assets within the enterprise, which can greatly improve the efficiency of asset inventory, enrich asset inventory methods, and activate enterprise operational data, reduce the enterprise's operating costs, and improve the enterprise's management level.

[0102] At the same time, it does not need to rely on other inventory tools, the cost is low, it is highly reusable and the inventory data is real and valid.

[0103] Another embodiment of the present invention provides a fixed asset data online processing device, such as Figure 2 As shown, the device comprises:

[0104] The login log data module 201 is used to obtain the domain account corresponding to the network device asset online, and obtain the corresponding login log data according to the domain account;

[0105] A matching module 202, used to match the login log data with the preset asset inventory configuration table;

[0106] The updating module 203 is used to update the preset asset inventory configuration table after matching the login log data into a valid inventory asset table.

[0107] The fixed asset data online processing device provided in this embodiment obtains the domain account corresponding to the network device asset online, obtains the corresponding login log data according to the domain account, then matches the login log data with the preset asset inventory configuration table, and finally updates the preset asset inventory configuration table after the login log data matching to a valid inventory asset table, thereby solving the technical problems of low inventory efficiency and high inventory cost caused by the existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations.

[0108] This embodiment obtains corresponding login log data through domain accounts to perform online detection of computer assets, which can improve data utilization and perform fully automatic inventory, greatly improving asset inventory efficiency, reducing enterprise operating costs, and improving computer asset data management level.

[0109] Furthermore, by using a data synchronization tool to clean and process the login log data according to preset field rules, the operational data within the enterprise (domain account login records) is cleaned and standardized, and used for online inventory of computer assets within the enterprise, which can greatly improve the efficiency of asset inventory, enrich asset inventory methods, and activate enterprise operational data, reduce the enterprise's operating costs, and improve the enterprise's management level.

[0110] At the same time, it does not need to rely on other inventory tools, the cost is low, it is highly reusable and the inventory data is real and valid.

[0111] Another embodiment of the present invention provides a fixed asset data online processing device, such as Figure 3 As shown, the device 10 includes:

[0112] One or more processors 110 and memory 120, Figure 3 A processor 110 is used as an example for description. The processor 110 and the memory 120 may be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0113] The processor 110 is used to complete various control logics of the device 10, and it can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a single-chip microcomputer, an ARM (Acorn RISCMachine) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component, or any combination of these components. In addition, the processor 110 can also be any traditional processor, microprocessor or state machine. The processor 110 can also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors combined with a DSP and / or any other such configuration.

[0114] The memory 120 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions corresponding to the method for online processing of fixed asset data in the embodiment of the present invention. The processor 110 executes various functional applications and data processing of the device 10 by running the non-volatile software programs, instructions and units stored in the memory 120, that is, implements the method for online processing of fixed asset data in the above method embodiment.

[0115] The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created according to the use of the device 10, etc. In addition, the memory 120 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include a memory remotely arranged relative to the processor 110, and these remote memories may be connected to the device 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0116] One or more units are stored in the memory 120, and when executed by one or more processors 110, the following steps are implemented:

[0117] Obtaining the domain account corresponding to the network device asset online, and obtaining corresponding login log data according to the domain account;

[0118] Matching the login log data with the preset asset inventory configuration table;

[0119] The preset asset inventory configuration table after matching the login log data is updated to a valid inventory asset table.

[0120] An embodiment of the present invention provides a non-volatile computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by one or more processors, the above steps S101 to S103 are implemented.

[0121] As an example, non-volatile storage media can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) as external cache memory. By way of illustration and not limitation, RAM can be obtained in many forms such as synchronous RAM (SRAM), dynamic RAM, (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The disclosed memory components or memories of the operating environment described herein are intended to include one or more of these and / or any other suitable types of memory.

[0122] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium, and the computer program can include the processes of the above-mentioned method embodiments when executed. The storage medium can be a memory, a disk, a floppy disk, a flash memory, an optical storage device, etc.

[0123] Compared with the prior art, the present invention obtains the domain account corresponding to the network device asset online, obtains the corresponding login log data according to the domain account, then matches the login log data with the preset asset inventory configuration table, and finally updates the preset asset inventory configuration table after the login log data is matched to a valid inventory asset table, thereby solving the technical problems of low inventory efficiency and high inventory cost caused by the existing online inventory of network devices through specific inventory commands, device response logs and interactive analysis between inventory service workstations.

[0124] This embodiment obtains corresponding login log data through domain accounts to perform online detection of computer assets, which can improve data utilization and perform fully automatic inventory, greatly improving asset inventory efficiency, reducing enterprise operating costs, and improving computer asset data management level.

[0125] Furthermore, by using a data synchronization tool to clean and process the login log data according to preset field rules, the operational data within the enterprise (domain account login records) is cleaned and standardized, and used for online inventory of computer assets within the enterprise, which can greatly improve the efficiency of asset inventory, enrich asset inventory methods, and activate enterprise operational data, reduce the enterprise's operating costs, and improve the enterprise's management level.

[0126] At the same time, it does not need to rely on other inventory tools, the cost is low, it is highly reusable and the inventory data is real and valid.

[0127] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

[0128] It should be noted that if software tools or components other than those of our company appear in the embodiments of the present application, they are only used for illustrative purposes and do not represent actual use.

Claims

1. A method for online processing of fixed asset data, characterized in that: include: Obtaining the domain account of the network device asset online, and obtaining corresponding login log data according to the domain account; Matching the login log data with the preset asset inventory configuration table; The preset asset inventory configuration table after matching the login log data is updated to a valid inventory asset table.

2. The method for online processing of fixed asset data according to claim 1, characterized in that: The steps of obtaining a domain account corresponding to a network device asset online and obtaining corresponding login log data according to the domain account include: Online synchronous acquisition of domain accounts corresponding to network equipment assets; The login log data corresponding to the domain account at a first preset time node is obtained.

3. The method for online processing of fixed asset data according to claim 2, characterized in that: The step of obtaining the login log data corresponding to the domain account at the first preset time node further includes: Cleaning and processing the login log data to determine that the login log data is valid login log data; The valid login log data is stored in the login data reference table in an accumulative manner.

4. The method for online processing of fixed asset data according to claim 3, characterized in that: The step of cleaning the login log data and determining that the login log data is valid login log data includes: Clean and process the login log data according to preset field rules using a data synchronization tool; Determine that the login log data is valid login log data.

5. The method for online processing of fixed asset data according to claim 4, characterized in that: The step of matching the login log data with the preset asset inventory configuration table includes: Configure the asset inventory configuration table according to the obtained online inventory validity days and inventory effectiveness flag; The valid login log data is matched with the asset inventory configuration table.

6. The method for online processing of fixed asset data according to claim 5, characterized in that: The step of matching the valid login log data with the asset inventory configuration table includes: Mapping the unique identification code of the valid login log data according to the acquired current inventory instruction; According to the unique identification code, the valid login log data corresponding to the valid days of the online inventory is matched with the asset inventory configuration table.

7. The method for online processing of fixed asset data according to claim 6, characterized in that: The step of updating the preset asset inventory configuration table after matching the login log data to a valid asset inventory table specifically includes: Updating the inventory time of the login log data and marking the inventory effectiveness mark; The preset asset inventory configuration table after update and matching is a valid asset inventory table.

8. A fixed asset data online processing device, characterized in that: include: A login log data module, used to obtain the domain account corresponding to the network device asset online, and obtain the corresponding login log data according to the domain account; A matching module, used to match the login log data with the preset asset inventory configuration table; An updating module is used to update the preset asset inventory configuration table after matching the login log data to a valid inventory asset table.

9. A fixed asset data online processing device, characterized in that: The device comprises at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the online fixed asset data processing method described in any one of claims 1-7.

10. A non-volatile computer-readable storage medium, characterized in that: The non-volatile computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by one or more processors, the one or more processors can execute the online fixed asset data processing method described in any one of claims 1-7.

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